Error correction of next-generation sequencing data and reliable estimation of HIV quasispecies

A study on factors influencing delayed sputum conversion in newly diagnosed pulmonary tuberculosis based on bacteriology and genomics

Conversion of sputum from positive to negative is one of the indicators to evaluate the efficacy of anti-tuberculosis treatment (ATT). We investigate the factors associated with delayed sputum conversion after 2 or 5 months of ATT from the perspectives of bacteriology and genomics. A retrospective study of sputum conversion in sputum positive 1782 pulmonary tuberculosis (PTB) was conducted from 2021 to 2022 in Beijing, China. We also designed a case-matched study including 24 pairs of delayed-sputum-conversion patients (DSCPs) and timely-sputum-conversion patients (TSCPs), and collect clinical isolates from DSCPs before and after ATT and initial isolates of TSCPs who successfully achieved sputum conversion to negative after 2 months of ATT. A total of 75 strains were conducted drug sensitivity testing (DST) of 13 anti-TB drugs and whole-genome sequencing (WGS) to analyze the risk factors of delayed conversion and the dynamics changes of drug resistance and genomics of Mycobacterium tuberculosis (MTB) during ATT. We found TSCPs have better treatment outcomes and whose initial isolates show lower levels of drug resistance. Clinical isolates of DSCPs showed dynamically changing of resistance phenotypes and intra-host heterogeneity. Single nucleotide polymorphism (SNP) profiles showed large differences between groups. The study provided insight into the bacteriological and genomic variation of delayed sputum conversion. It would be helpful for early indication of sputum conversion and guidance on ATT.

Methods to improve the accuracy of next-generation sequencing

Next-generation sequencing (NGS) is present in all fields of life science, which has greatly promoted the development of basic research while being gradually applied in clinical diagnosis. However, the cost and throughput advantages of next-generation sequencing are offset by large tradeoffs with respect to read length and accuracy. Specifically, its high error rate makes it extremely difficult to detect SNPs or low-abundance mutations, limiting its clinical applications, such as pharmacogenomics studies primarily based on SNP and early clinical diagnosis primarily based on low abundance mutations. Currently, Sanger sequencing is still considered to be the gold standard due to its high accuracy, so the results of next-generation sequencing require verification by Sanger sequencing in clinical practice. In order to maintain high quality next-generation sequencing data, a variety of improvements at the levels of template preparation, sequencing strategy and data processing have been developed. This study summarized the general procedures of next-generation sequencing platforms, highlighting the improvements involved in eliminating errors at each step. Furthermore, the challenges and future development of next-generation sequencing in clinical application was discussed.

K-Mer Spectrum-Based Error Correction Algorithm for Next-Generation Sequencing Data

In the mid-1970s, the first-generation sequencing technique (Sanger) was created. It used Advanced BioSystems sequencing devices and Beckman's GeXP genetic testing technology. The second-generation sequencing (2GS) technique arrived just several years after the first human genome was published in 2003. 2GS devices are very quicker than Sanger sequencing equipment, with considerably cheaper manufacturing costs and far higher throughput in the form of short reads. The third-generation sequencing (3GS) method, initially introduced in 2005, offers further reduced manufacturing costs and higher throughput. Even though sequencing technique has result generations, it is error-prone due to a large number of reads. The study of this massive amount of data will aid in the decoding of life secrets, the detection of infections, the development of improved crops, and the improvement of life quality, among other things. This is a challenging task, which is complicated not just by a large number of reads and by the occurrence of sequencing mistakes. As a result, error correction is a crucial duty in data processing; it entails identifying and correcting read errors. Various k-spectrum-based error correction algorithms' performance can be influenced by a variety of characteristics like coverage depth, read length, and genome size, as demonstrated in this work. As a result, time and effort must be put into selecting acceptable approaches for error correction of certain NGS data.

Current Methods for Recombination Detection in Bacteria

The role of genetic exchanges, i.e., homologous recombination (HR) and horizontal gene transfer (HGT), in bacteria cannot be overestimated for it is a pivotal mechanism leading to their evolution and adaptation, thus, tracking the signs of recombination and HGT events is importance both for fundamental and applied science. To date, dozens of bioinformatics tools for revealing recombination signals are available, however, their pros and cons as well as the spectra of solvable tasks have not yet been systematically reviewed. Moreover, there are two major groups of software. One aims to infer evidence of HR, while the other only deals with horizontal gene transfer (HGT). However, despite seemingly different goals, all the methods use similar algorithmic approaches, and the processes are interconnected in terms of genomic evolution influencing each other. In this review, we propose a classification of novel instruments for both HR and HGT detection based on the genomic consequences of recombination. In this context, we summarize available methodologies paying particular attention to the type of traceable events for which a certain program has been designed.

Detection of Chimeric Cellular: HIV mRNAs Generated Through Aberrant Splicing in HIV-1 Latently Infected Resting CD4+ T Cells

Latent HIV-1 provirus in infected individuals on suppressive therapy does not always remain transcriptionally silent. Both HIV-1 LTR and human gene promoter derived transcriptional events can contribute HIV-1 sequences to the mRNA produced in the cell. In addition, chimeric cellular:HIV mRNA can arise through readthrough transcription and aberrant splicing. Using target enrichment coupled to the Illumina Mi-Seq and PacBio RS II platforms, we show that 3’ LTR activation is frequent in latently infected cells from both the CCL19-induced primary cell model of HIV-1 latency as well as ex vivo samples. In both systems of latent HIV-1 infection, we detected several chimeric species that were generated via activation of a cryptic splice donor site in the 5’ LTR of HIV-1. Aberrant splicing involving the major HIV-1 splice donor sites, SD1 and SD4 disrupts post-transcriptional processing of the gene in which HIV-1 is integrated. In the primary cell model of HIV-1 latency, Tat-encoding sequences are incorporated into the chimeric mRNA transcripts through the use of SD4. Our study unravels clues to the characteristics of HIV-1 integrants that promote formation of chimeric cellular:HIV mRNA and improves the understanding of the HIV-1 RNA footprint in latently infected cells.

New aspects of the Virus Life Cycle and Clinical Utility of Next Generation Sequencing based HIV-1 Resistance Testing in the Genomic, the Proviral and the Viral Reservoir of Peripheral Blood Mononuclear Cells

BACKGROUND

Typically, genotypic resistance testing is recommended at the start of antiretroviral therapy and is even mandatory in cases of virologic failure. The material of choice is plasma viral RNA. However, in patients with low viremia (viral load < 500 copies/ml), resistance testing by population-based sequencing is very difficult.

OBJECTIVE

Therefore, we aimed to investigate whether next generation sequencing (NGS) from proviral DNA and RNA could be an alternative.

MATERIAL AND METHODS

EDTA blood samples (n = 36) from routine clinical viral load testing were used for the study. Viral loads ranged from 96 to 390,000 copies/mL, with 100% of samples having low viremia. Distribution of subtypes A (n = 2), B (n = 16), C (n = 4), D (n = 2), G (1), CRF02 AG (n = 5), CRF01 AE (n = 5), undefined/mixed (n = 4). The extracted consensus sequences were uploaded to the Stanford HIV Drug Resistance Data Base and Geno2pheno for online analysis of drug resistance mutations and resistance factors.

RESULTS

A total of 2476 variants or drug resistance mutations (DRMs) were detected with Sanger sequencing, compared with 2892 variants with NGS. An average of 822/1008 variants were identified in plasma viral RNA by Sanger or NGS sequencing, 834/956 in cellular viral RNA, and 820/928 in cellular viral DNA.

CONCLUSIONS

Both methods are well suited for the detection of HIV substitutions or drug resistance mutations. Our results suggest that cellular RNA or cellular viral DNA is an informative alternative to plasma viral RNA for variant detection in patients with low viremia, as shown by the high correlation of variants in the different viral pools. And we show that by using UDS, a plus of two DRMs per patient becomes visible and that can make a big difference in the assessment of the expected resistance behavior of the virus.

Binnacle: Using Scaffolds to Improve the Contiguity and Quality of Metagenomic Bins

High-throughput sequencing has revolutionized the field of microbiology, however, reconstructing complete genomes of organisms from whole metagenomic shotgun sequencing data remains a challenge. Recovered genomes are often highly fragmented, due to uneven abundances of organisms, repeats within and across genomes, sequencing errors, and strain-level variation. To address the fragmented nature of metagenomic assemblies, scientists rely on a process called binning, which clusters together contigs inferred to originate from the same organism. Existing binning algorithms use oligonucleotide frequencies and contig abundance (coverage) within and across samples to group together contigs from the same organism. However, these algorithms often miss short contigs and contigs from regions with unusual coverage or DNA composition characteristics, such as mobile elements. Here, we propose that information from assembly graphs can assist current strategies for metagenomic binning. We use MetaCarvel, a metagenomic scaffolding tool, to construct assembly graphs where contigs are nodes and edges are inferred based on paired-end reads. We developed a tool, Binnacle, that extracts information from the assembly graphs and clusters scaffolds into comprehensive bins. Binnacle also provides wrapper scripts to integrate with existing binning methods. The Binnacle pipeline can be found on GitHub (https://github.com/marbl/binnacle). We show that binning graph-based scaffolds, rather than contigs, improves the contiguity and quality of the resulting bins, and captures a broader set of the genes of the organisms being reconstructed.

ESREEM: Efficient Short Reads Error Estimation Computational Model for Next-generation Genome Sequencing

Aims:

To assess the error profile in NGS data, generated from high throughput sequencing machines.

Background:

Short-read sequencing data from Next Generation Sequencing (NGS) are currently being generated by a number of research projects. Depicting the errors produced by NGS platforms and expressing accurate genetic variation from reads are two inter-dependent phases. It has high significance in various analyses, such as genome sequence assembly, SNPs calling, evolutionary studies, and haplotype inference. The systematic and random errors show incidence profile for each of the sequencing platforms i.e. Illumina sequencing, Pacific Biosciences, 454 pyrosequencing, Complete Genomics DNA nanoball sequencing, Ion Torrent sequencing, and Oxford Nanopore sequencing. Advances in NGS deliver galactic data with the addition of errors. Some ratio of these errors may emulate genuine true biological signals i.e., mutation, and may subsequently negate the results. Various independent applications have been proposed to correct the sequencing errors. Systematic analysis of these algorithms shows that state-of-the-art models are missing.

Objective:

In this paper, an effcient error estimation computational model called ESREEM is proposed to assess the error rates in NGS data.

Methods:

The proposed model prospects the analysis that there exists a true linear regression association between the number of reads containing errors and the number of reads sequenced. The model is based on a probabilistic error model integrated with the Hidden Markov Model (HMM).

Result:

The proposed model is evaluated on several benchmark datasets and the results obtained are compared with state-of-the-art algorithms.

Conclusions:

Experimental results analyses show that the proposed model efficiently estimates errors and runs in less time as compared to others.

Recommendations for the introduction of metagenomic high-throughput sequencing in clinical virology, part I: Wet lab procedure

Metagenomic high-throughput sequencing (mHTS) is a hypothesis-free, universal pathogen detection technique for determination of the DNA/RNA sequences in a variety of sample types and infectious syndromes. mHTS is still in its early stages of translating into clinical application. To support the development, implementation and standardization of mHTS procedures for virus diagnostics, the European Society for Clinical Virology (ESCV) Network on Next-Generation Sequencing (ENNGS) has been established. The aim of ENNGS is to bring together professionals involved in mHTS for viral diagnostics to share methodologies and experiences, and to develop application recommendations. This manuscript aims to provide practical recommendations for the wet lab procedures necessary for implementation of mHTS for virus diagnostics and to give recommendations for development and validation of laboratory methods, including mHTS quality assurance, control and quality assessment protocols.

Comparison of Serum Hepatitis B Virus RNA Levels and Quasispecies Evolution Patterns between Entecavir and Pegylated-Interferon Mono-treatment in Chronic Hepatitis B Patients

Hepatitis B virus (HBV) RNA may independently predict virological and serological response. This study aimed to compare dynamic changes in serum HBV RNA levels and HBV quasispecies evolution patterns between entecavir and pegylated-interferon mono-treatment in chronic hepatitis B patients and to determine the clinical significance during treatment. TaqMan real-time PCR was used for quantitative analysis. HBV RNA levels were retrospectively determined in serial serum samples from 178 chronic hepatitis B patients who received either entecavir or pegylated-interferon treatment.

Hepatitis B virus (HBV) RNA may independently predict virological and serological response. This study aimed to compare dynamic changes in serum HBV RNA levels and HBV quasispecies evolution patterns between entecavir and pegylated-interferon mono-treatment in chronic hepatitis B patients and to determine the clinical significance during treatment. TaqMan real-time PCR was used for quantitative analysis. HBV RNA levels were retrospectively determined in serial serum samples from 178 chronic hepatitis B patients who received either entecavir or pegylated-interferon treatment. Both serum HBV DNA and RNA quasispecies were analyzed via next-generation sequencing. Receiver operating characteristics (ROC) analysis was performed to evaluate the prediction value of individual biomarkers for hepatitis B e antigen (HBeAg) seroconversion. Patients who received pegylated-interferon treatment showed stronger declines in HBV RNA levels than did those who received entecavir treatment. Serum HBV RNA levels were lower in patients with subsequent HBeAg seroconversion. At baseline, the level of HBV RNA was better than other indicators in predicting HBeAg seroconversion. Moreover, the predictive value of serum HBV RNA levels was better in the entecavir group. Baseline HBV RNA exhibited a significantly higher genetic diversity than HBV DNA and had a significant decline after 4 weeks of entecavir treatment. Higher baseline genetic diversity may result in a better outcome in pegylated-interferon-treated patients. Serum HBV RNA levels showed different decline kinetics, and HBV RNA quasispecies showed different evolution patterns in entecavir and pegylated-interferon mono-treatment. Taken together, serum HBV RNA may serve as a promising biomarker of HBeAg seroconversion in patients during antiviral treatment.

Long-read individual-molecule sequencing reveals CRISPR-induced genetic heterogeneity in human ESCs

Quantifying the genetic heterogeneity of a cell population is essential to understanding of biological systems. We develop a universal method to label individual DNA molecules for single-base-resolution haplotype-resolved quantitative characterization of diverse types of rare variants, with frequency as low as 4 × 10-5, using both short- or long-read sequencing platforms. It provides the first quantitative evidence of persistent nonrandom large structural variants and an increase in single-nucleotide variants at the on-target locus following repair of double-strand breaks induced by CRISPR-Cas9 in human embryonic stem cells.

Applying next-generation sequencing to unravel the mutational landscape in viral quasispecies

Next-generation sequencing (NGS) has revolutionized the scale and depth of biomedical sciences. Because of its unique ability for the detection of sub-clonal variants within genetically diverse populations, NGS has been successfully applied to analyze and quantify the exceptionally-high diversity within viral quasispecies, and many low-frequency drug- or vaccine-resistant mutations of therapeutic importance have been discovered. Although many works have intensively discussed the latest NGS approaches and applications in general, none of them has focused on applying NGS in viral quasispecies studies, mostly due to the limited ability of current NGS technologies to accurately detect and quantify rare viral variants. Here, we summarize several error-correction strategies that have been developed to enhance the detection accuracy of minority variants. We also discuss critical considerations for preparing a sequencing library from viral RNAs and for analyzing NGS data to unravel the mutational landscape.

The population structure of Rose rosette virus in the USA

Rose rosette virus (RRV) (genus Emaravirus) is the causal agent of the homonymous disease, the most destructive malady of roses in the USA. Although the importance of the disease is recognized, little sequence information and no full genomes are available for RRV, a multi-segmented RNA virus. To better understand the population structure of the virus we implemented a Hi-Plex PCR amplicon high-throughput sequencing approach to sequence all 7 segments and to quantify polymorphisms in 91 RRV isolates collected from 16 states in the USA. Analysis revealed insertion/deletion (indel) polymorphisms primarily in the 5' and 3' non-coding, but also within coding regions, including some resulting in changes of protein length. Phylogenetic analysis showed little geographical structuring, suggesting that topography does not have a strong influence on virus evolution. Overall, the virus populations were homogeneous, possibly because of regular movement of plants, the recent emergence of RRV and/or because the virus is under strong purification selection to preserve its integrity and biological functions.

Single genome sequencing of near full-length HIV-1 RNA using a limiting dilution approach

Sequencing very long stretches of the HIV-1 genome can advance studies on virus evolution and in vivo recombination but remains technically challenging. We developed an efficient procedure to sequence near full-length HIV-1 RNA using a two-amplicon approach. The whole genome was successfully amplified for 107 (88%) of 121 plasma samples including samples from patients infected with HIV-1 subtype A1, B, C, D, F1, G, H, CRF01_AE and CRF02_AG. For the 17 samples with a viral load below 1000 c/ml and the 104 samples with a viral load above 1000 c/ml, the amplification efficiency was respectively 53% and 94%. The sensitivity of the method was further evaluated using limiting dilution of RNA extracted from a plasma pool containing an equimolar mixture of three HIV-1 subtypes (B, C and CRF02_AG) and diluted before and after cDNA generation. Both RNA and cDNA dilution showed comparable sensitivity and equal accuracy in reflecting the subtype distribution of the plasma pool. One single event of in vitro recombination was detected amongst the 41 sequences obtained after cDNA dilution but no indications for in vitro recombination were found after RNA dilution. In conclusion, a two-amplicon strategy and limiting dilution of viral RNA followed by reverse transcription, nested PCR and Sanger sequencing, allows near full genome sequencing of individual HIV-1 RNA molecules. This method will be a valuable tool in the study of virus evolution and recombination.

Hepatitis C virus (HCV) genotype 1b displays higher genetic variability of hypervariable region 1 (HVR1) than genotype 3

Hepatitis C virus (HCV) is characterized by high genetic variability, which is manifested both at the inter-host and intra-host levels. However, its role in the clinical course of infection is less obvious. The aim of the present study was to determine the genetic variability of HCV HVR1 (hypervariable region 1) of genotype 1b and 3 in plasma of blood donors in the early seronegative stage of infection (HCV-RNA+, anti-HCV−) and in samples from chronically infected patients using next-generation sequencing. Sequencing errors were corrected, and haplotypes inferred using the ShoRAH software. Genetic diversity parameters (intra-host number of variants, number of nucleotide substitutions and diversity per site) were assessed by DNA SP and MEGA. During the early infection, the number of variants were significantly lower in subjects infected with genotype 3 than with genotype 1b (p < 0.02). Similarly, intra-host number of variants, number of nucleotide substitutions and diversity per site were lower in genotype 3 chronic infection (p < 0.0005). In addition, early infection was characterized by significantly lower HVR1 variability values (p < 0.04) when compared to chronic infection for both genotypes. It seems that the observed differences in HVR1 variability represent an inherent property of particular viral genotypes.

Persistent Infection of African Buffalo (Syncerus caffer) with Foot-and-Mouth Disease Virus: Limited Viral Evolution and No Evidence of Antibody Neutralization Escape

African buffaloes (Syncerus caffer) are the principal "carrier" hosts of foot-and-mouth disease virus (FMDV). Currently, the epithelia and lymphoid germinal centers of the oropharynx have been identified as sites for FMDV persistence. We carried out studies in FMDV SAT1 persistently infected buffaloes to characterize the diversity of viruses in oropharyngeal epithelia, germinal centers, probang samples (oropharyngeal scrapings), and tonsil swabs to determine if sufficient virus variation is generated during persistence for immune escape. Most sequencing reads of the VP1 coding region of the SAT1 virus inoculum clustered around 2 subpopulations differing by 22 single-nucleotide variants of intermediate frequency. Similarly, most sequences from oropharynx tissue clustered into two subpopulations, albeit with different proportions, depending on the day postinfection (dpi). There was a significant difference between the populations of viruses in the inoculum and in lymphoid tissue taken at 35 dpi. Thereafter, until 400 dpi, no significant variation was detected in the viral populations in samples from individual animals, germinal centers, and epithelial tissues. Deep sequencing of virus from probang or tonsil swab samples harvested prior to postmortem showed less within-sample variability of VP1 than that of tissue sample sequences analyzed at the same time. Importantly, there was no significant difference in the ability of sera collected between 14 and 400 dpi to neutralize the inoculum or viruses isolated at later time points in the study from the same animal. Therefore, based on this study, there is no evidence of escape from antibody neutralization contributing to FMDV persistent infection in African buffalo.IMPORTANCE Foot-and-mouth disease virus (FMDV) is a highly contagious virus of cloven-hoofed animals and is recognized as the most important constraint to international trade in animals and animal products. African buffaloes (Syncerus caffer) are efficient carriers of FMDV, and it has been proposed that new virus variants are produced in buffalo during the prolonged carriage after acute infection, which may spread to cause disease in livestock populations. Here, we show that despite an accumulation of low-frequency sequence variants over time, there is no evidence of significant antigenic variation leading to immune escape. Therefore, carrier buffalo are unlikely to be a major source of new virus variants.

PCR Amplification Strategies Towards Full-length HIV-1 Genome Sequencing

The advent of next-generation sequencing has enabled greater resolution of viral diversity and improved feasibility of full viral genome sequencing allowing routine HIV-1 full genome sequencing in both research and diagnostic settings. Regardless of the sequencing platform selected, successful PCR amplification of the HIV-1 genome is essential for sequencing template preparation. As such, full HIV-1 genome amplification is a crucial step in dictating the successful and reliable sequencing downstream. Here we reviewed existing PCR protocols leading to HIV-1 full genome sequencing. In addition to the discussion on basic considerations on relevant PCR design, the advantages as well as the pitfalls of the published protocols were reviewed.

Barcode-free next-generation sequencing error validation for ultra-rare variant detection

The advent of next-generation sequencing (NGS) has accelerated biomedical research by enabling the high-throughput analysis of DNA sequences at a very low cost. However, NGS has limitations in detecting rare-frequency variants (< 1%) because of high sequencing errors (> 0.1~1%). NGS errors could be filtered out using molecular barcodes, by comparing read replicates among those with the same barcodes. Accordingly, these barcoding methods require redundant reads of non-target sequences, resulting in high sequencing cost. Here, we present a cost-effective NGS error validation method in a barcode-free manner. By physically extracting and individually amplifying the DNA clones of erroneous reads, we distinguish true variants of frequency > 0.003% from the systematic NGS error and selectively validate NGS error after NGS. We achieve a PCR-induced error rate of 2.5×10⁻⁶ per base per doubling event, using 10 times less sequencing reads compared to those from previous studies.

Next generation sequencing has difficulty in detecting rare-frequency variants due to high sequencing errors. Here the authors present a barcode-free error validation method that physically extracts erroneous reads to identify true variants.

Link between the numbers of particles and variants founding new HIV-1 infections depends on the timing of transmission

Understanding which HIV-1 variants are most likely to be transmitted is important for vaccine design and predicting virus evolution. Since most infections are founded by single variants, it has been suggested that selection at transmission has a key role in governing which variants are transmitted. We show that the composition of the viral population within the donor at the time of transmission is also important. To support this argument, we developed a probabilistic model describing HIV-1 transmission in an untreated population, and parameterised the model using both within-host next generation sequencing data and population-level epidemiological data on heterosexual transmission. The most basic HIV-1 transmission models cannot explain simultaneously the low probability of transmission and the non-negligible proportion of infections founded by multiple variants. In our model, transmission can only occur when environmental conditions are appropriate (e.g. abrasions are present in the genital tract of the potential recipient), allowing these observations to be reconciled. As well as reproducing features of transmission in real populations, our model demonstrates that, contrary to expectation, there is not a simple link between the number of viral variants and the number of viral particles founding each new infection. These quantities depend on the timing of transmission, and infections can be founded with small numbers of variants yet large numbers of particles. Including selection, or a bias towards early transmission (e.g. due to treatment), acts to enhance this conclusion. In addition, we find that infections initiated by multiple variants are most likely to have derived from donors with intermediate set-point viral loads, and not from individuals with high set-point viral loads as might be expected. We therefore emphasise the importance of considering viral diversity in donors, and the timings of transmissions, when trying to discern the complex factors governing single or multiple variant transmission.

Inter- and Intra-Host Nucleotide Variations in Hepatitis A Virus in Culture and Clinical Samples Detected by Next-Generation Sequencing

The accurate virus detection, strain discrimination, and source attribution of contaminated food items remains a persistent challenge because of the high mutation rates anticipated to occur in foodborne RNA viruses, such as hepatitis A virus (HAV). This has led to predictions of the existence of more than one sequence variant between the hosts (inter-host) or within an individual host (intra-host). However, there have been no reports of intra-host variants from an infected single individual, and little is known about the accuracy of the single nucleotide variations (SNVs) calling with various methods. In this study, the presence and identity of viral SNVs, either between HAV clinical specimens or among a series of samples derived from HAV clone1-infected FRhK4 cells, were determined following analyses of nucleotide sequences generated using next-generation sequencing (NGS) and pyrosequencing methods. The results demonstrate the co-existence of inter- and intra-host variants both in the clinical specimens and the cultured samples. The discovery and confirmation of multi-viral RNAs in an infected individual is dependent on the strain discrimination at the SNV level, and critical for successful outbreak traceback and source attribution investigations. The detection of SNVs in a time series of HAV infected FRhK4 cells improved our understanding on the mutation dynamics determined probably by different selective pressures. Additionally, it demonstrated that NGS could potentially provide a valuable investigative approach toward SNV detection and identification for other RNA viruses.

Detection of minority drug resistant mutations in Malawian HIV-1 subtype C-positive patients initiating and on first-line antiretroviral therapy

Background

Minority drug resistance mutations (DRMs) that are often missed by Sanger sequencing are clinically significant, as they can cause virologic failure in individuals treated with antiretroviral therapy (ART) drugs.

Objective

This study aimed to estimate the prevalence of minor DRMs among patients enrolled in a Malawi HIV drug resistance monitoring survey at baseline and at one year after initiation of ART.

Methods

Forty-one plasma specimens collected from HIV-1 subtype C-positive patients and seven clonal control samples were analysed using ultra-deep sequencing technology.

Results

Deep sequencing identified all 72 DRMs detected by Sanger sequencing at the level of ≥20% and 79 additional minority DRMs at the level of < 20% from the 41 Malawian clinical specimens. Overall, DRMs were detected in 85% of pre-ART and 90.5% of virologic failure patients by deep sequencing. Among pre-ART patients, deep sequencing identified a statistically significant higher prevalence of DRMs to nucleoside reverse transcriptase inhibitors (NRTIs) compared with Sanger sequencing. The difference was mainly due to the high prevalence of minority K65R and M184I mutations. Most virologic failure patients harboured DRMs against both NRTIs and non-nucleoside reverse transcriptase inhibitors (NNRTIs). These minority DRMs contributed to the increased or enhanced virologic failures in these patients.

Conclusion

The results revealed the presence of minority DRMs to NRTIs and NNRTIs in specimens collected at baseline and virologic failure time points. These minority DRMs not only increased resistance levels to NRTIs and NNRTIs for the prescribed ART, but also expanded resistance to additional major first-line ART drugs. This study suggested that drug resistance testing that uses more sensitive technologies, is needed in this setting.

Enhancing the accuracy of next-generation sequencing for detecting rare and subclonal mutations

Mutations, the fuel of evolution, are first manifested as rare DNA changes within a population of cells. Although next-generation sequencing (NGS) technologies have revolutionized the study of genomic variation between species and individual organisms, most have limited ability to accurately detect and quantify rare variants among the different genome copies in heterogeneous mixtures of cells or molecules. We describe the technical challenges in characterizing subclonal variants using conventional NGS protocols and the recent development of error correction strategies, both computational and experimental, including consensus sequencing of single DNA molecules. We also highlight major applications for low-frequency mutation detection in science and medicine, describe emerging methodologies and provide our vision for the future of DNA sequencing.

A penalized regression approach to haplotype reconstruction of viral populations arising in early HIV/SIV infection

Motivation

Next generation sequencing (NGS) has been increasingly applied to characterize viral evolution during HIV and SIV infections. In particular, NGS datasets sampled during the initial months of infection are characterized by relatively low levels of diversity as well as convergent evolution at multiple loci dispersed across the viral genome. Consequently, fully characterizing viral evolution from NGS datasets requires haplotype reconstruction across large regions of the viral genome. Existing haplotype reconstruction algorithms have not been developed with the particular characteristics of early HIV/SIV infection in mind, raising the possibility that better performance could be achieved through a specifically designed algorithm.

Results

Here, we introduce a haplotype reconstruction algorithm, RegressHaplo, specifically designed for low diversity and convergent evolution regimes. The algorithm uses a penalized regression that balances a data fitting term with a penalty term that encourages solutions with few haplotypes. The regression covariates are a large set of potential haplotypes and fitting the regression is made computationally feasible by the low diversity setting. Using simulated and in vivo datasets, we compare RegressHaplo to PredictHaplo and QuRe, two existing haplotype reconstruction algorithms. RegressHaplo performs better than these algorithms on simulated datasets with relatively low diversity levels. We suggest RegressHaplo as a novel tool for the investigation of early infection HIV/SIV datasets and, more generally, low diversity viral NGS datasets.

Contact

sr286@georgetown.edu.

Availability and Implementation

https://github.com/SLeviyang/RegressHaplo.

Paper-based detection of HIV-1 drug resistance using isothermal amplification and an oligonucleotide ligation assay

Regular HIV-1 viral load monitoring is the standard of care to assess antiretroviral therapy effectiveness in resource-rich settings. Persistently elevated viral loads indicate virologic failure (VF), which warrants HIV drug resistance testing (HIVDRT) to allow individualized regimen switches. However, in settings lacking access to HIVDRT, clinical decisions are often made based on symptoms, leading to unnecessary therapy switches and increased costs of care. This work presents a proof-of-concept assay to detect M184V, the most common drug resistance mutation after first-line antiretroviral therapy failure, in a paper format. The first step isothermally amplifies a section of HIV-1 reverse transcriptase containing M184V using a recombinase polymerase amplification (RPA) assay. Then, an oligonucleotide ligation assay (OLA) is used to selectively label the mutant and wild type amplified sequences. Finally, a lateral flow enzyme-linked immunosorbent assay (ELISA) differentiates between OLA-labeled products with or without M184V. Our method shows 100% specificity and 100% sensitivity when tested with samples that contained 200 copies of mutant DNA and 800 copies of wild type DNA prior to amplification. When integrated with sample preparation, this method may detect HIV-1 drug resistance at a low cost and at a rural hospital laboratory.

Separation and assembly of deep sequencing data into discrete sub-population genomes

Sequence heterogeneity is a common characteristic of RNA viruses that is often referred to as sub-populations or quasispecies. Traditional techniques used for assembly of short sequence reads produced by deep sequencing, such as de-novo assemblers, ignore the underlying diversity. Here, we introduce a novel algorithm that simultaneously assembles discrete sequences of multiple genomes present in populations. Using in silico data we were able to detect populations at as low as 0.1% frequency with complete global genome reconstruction and in a single sample detected 16 resolved sequences with no mismatches. We also applied the algorithm to high throughput sequencing data obtained for viruses present in sewage samples and successfully detected multiple sub-populations and recombination events in these diverse mixtures. High sensitivity of the algorithm also enables genomic analysis of heterogeneous pathogen genomes from patient samples and accurate detection of intra-host diversity, enabling not just basic research in personalized medicine but also accurate diagnostics and monitoring drug therapies, which are critical in clinical and regulatory decision-making process.

A comparative study on the characterization of hepatitis B virus quasispecies by clone-based sequencing and third-generation sequencing

Hepatitis B virus (HBV) has a high mutation rate due to the extremely high replication rate and the proofreading deficiency during reverse transcription. The generated variants with genetic heterogeneity are described as viral quasispecies (QS). Clone-based sequencing (CBS) is thought to be the ‘gold standard’ for assessing QS complexity and diversity of HBV, but an important issue about CBS is cost-effectiveness and laborious. In this study, we investigated the utility of the third-generation sequencing (TGS) DNA sequencing to characterize genetic heterogeneity of HBV QS and assessed the possible contribution of TGS technology in HBV QS studies. Parallel experiments including 3 control samples, which consisted of HBV full gene genotype B and genotype C plasmids, and 10 patients samples were performed by using CBS and TGS to analyze HBV whole-genome QS. Characterization of QS heterogeneity was conducted by using comprehensive statistical analysis. The results showed that TGS had a high consistency with CBS when measuring the complexity and diversity of QS. In addition, to detect rare variants, there were strong advantages conferred by TGS. In summary, TGS was considered to be practicable in HBV QS studies and it might have a relevant role in the clinical management of HBV infection in the future.

Deep sequencing in the management of hepatitis virus infections

The hepatitis viruses represent a major public health problem worldwide. Procedures for characterization of the genomic composition of their populations, accurate diagnosis, identification of multiple infections, and information on inhibitor-escape mutants for treatment decisions are needed. Deep sequencing methodologies are extremely useful for these viruses since they replicate as complex and dynamic quasispecies swarms whose complexity and mutant composition are biologically relevant traits. Population complexity is a major challenge for disease prevention and control, but also an opportunity to distinguish among related but phenotypically distinct variants that might anticipate disease progression and treatment outcome. Detailed characterization of mutant spectra should permit choosing better treatment options, given the increasing number of new antiviral inhibitors available. In the present review we briefly summarize our experience on the use of deep sequencing for the management of hepatitis virus infections, particularly for hepatitis B and C viruses, and outline some possible new applications of deep sequencing for these important human pathogens.

Analysis of intra-host genetic diversity of Prunus necrotic ringspot virus (PNRSV) using amplicon next generation sequencing

PCR amplicon next generation sequencing (NGS) analysis offers a broadly applicable and targeted approach to detect populations of both high- or low-frequency virus variants in one or more plant samples. In this study, amplicon NGS was used to explore the diversity of the tripartite genome virus, Prunus necrotic ringspot virus (PNRSV) from 53 PNRSV-infected trees using amplicons from conserved gene regions of each of PNRSV RNA1, RNA2 and RNA3. Sequencing of the amplicons from 53 PNRSV-infected trees revealed differing levels of polymorphism across the three different components of the PNRSV genome with a total number of 5040, 2083 and 5486 sequence variants observed for RNA1, RNA2 and RNA3 respectively. The RNA2 had the lowest diversity of sequences compared to RNA1 and RNA3, reflecting the lack of flexibility tolerated by the replicase gene that is encoded by this RNA component. Distinct PNRSV phylo-groups, consisting of closely related clusters of sequence variants, were observed in each of PNRSV RNA1, RNA2 and RNA3. Most plant samples had a single phylo-group for each RNA component. Haplotype network analysis showed that smaller clusters of PNRSV sequence variants were genetically connected to the largest sequence variant cluster within a phylo-group of each RNA component. Some plant samples had sequence variants occurring in multiple PNRSV phylo-groups in at least one of each RNA and these phylo-groups formed distinct clades that represent PNRSV genetic strains. Variants within the same phylo-group of each Prunus plant sample had ≥97% similarity and phylo-groups within a Prunus plant sample and between samples had less ≤97% similarity. Based on the analysis of diversity, a definition of a PNRSV genetic strain was proposed. The proposed definition was applied to determine the number of PNRSV genetic strains in each of the plant samples and the complexity in defining genetic strains in multipartite genome viruses was explored.

Clinical features and viral quasispecies characteristics associated with infection by the hepatitis B virus G145R immune escape mutant

Coexistence of the hepatitis B surface antigen (HBsAg) and hepatitis B surface antibody (anti-HBs) is an uncommon phenomenon, and the underlying mechanisms remain largely unknown. Amino-acid (aa) substitution from glycine to arginine at aa 145 (G145R), in the major hydrophilic region, has been reported in patients with HBsAg and anti-HBs coexistence. However, there is limited knowledge about the clinical features and viral quasispecies characteristics associated with G145R mutant hepatitis B virus (HBV) infection. We herein describe the dynamic changes in the serological and virological markers in a case of hepatitis B with coexisting HBsAg and anti-HBs, caused by a G145R immune escape mutant (genotype C). Entecavir was administered during the 4th week after admission. Alanine aminotransferase peaked in the 16th week, while both the HBsAg and HBeAg declined rapidly. HBsAg clearance and hepatitis B e antigen (HBeAg)/hepatitis B e antibody (anti-HBe) seroconversion were achieved in the 36th week, and then entecavir was withdrawn. A follow-up of 96 weeks showed that HBV DNA remained undetectable and that anti-HBs was maintained above 100 mIU/mL. The quasispecies characteristics of the G145R mutant HBV were investigated via ultra-deep sequencing. The complexity and genetic distance of the S and RT regions were much higher in the 8th week than at baseline or in the 4th week. Moreover, the frequencies of mutations (L173P, Q181R and A184V) in cytotoxic T lymphocyte epitopes increased before entecavir treatment. These findings extend understanding of the evolution of HBV under host immune pressure and of the clinical outcomes of affected patients.

Error baseline rates of five sample preparation methods used to characterize RNA virus populations

Individual RNA viruses typically occur as populations of genomes that differ slightly from each other due to mutations introduced by the error-prone viral polymerase. Understanding the variability of RNA virus genome populations is critical for understanding virus evolution because individual mutant genomes may gain evolutionary selective advantages and give rise to dominant subpopulations, possibly even leading to the emergence of viruses resistant to medical countermeasures. Reverse transcription of virus genome populations followed by next-generation sequencing is the only available method to characterize variation for RNA viruses. However, both steps may lead to the introduction of artificial mutations, thereby skewing the data. To better understand how such errors are introduced during sample preparation, we determined and compared error baseline rates of five different sample preparation methods by analyzing in vitro transcribed Ebola virus RNA from an artificial plasmid-based system. These methods included: shotgun sequencing from plasmid DNA or in vitro transcribed RNA as a basic “no amplification” method, amplicon sequencing from the plasmid DNA or in vitro transcribed RNA as a “targeted” amplification method, sequence-independent single-primer amplification (SISPA) as a “random” amplification method, rolling circle reverse transcription sequencing (CirSeq) as an advanced “no amplification” method, and Illumina TruSeq RNA Access as a “targeted” enrichment method. The measured error frequencies indicate that RNA Access offers the best tradeoff between sensitivity and sample preparation error (1.4⁻⁵) of all compared methods.

Error rates, PCR recombination, and sampling depth in HIV-1 whole genome deep sequencing

Deep sequencing is a powerful and cost-effective tool to characterize the genetic diversity and evolution of virus populations. While modern sequencing instruments readily cover viral genomes many thousand fold and very rare variants can in principle be detected, sequencing errors, amplification biases, and other artifacts can limit sensitivity and complicate data interpretation. For this reason, the number of studies using whole genome deep sequencing to characterize viral quasi-species in clinical samples is still limited. We have previously undertaken a large scale whole genome deep sequencing study of HIV-1 populations. Here we discuss the challenges, error profiles, control experiments, and computational test we developed to quantify the accuracy of variant frequency estimation.

Promises and pitfalls of Illumina sequencing for HIV resistance genotyping

Genetic sequencing ("genotyping") plays a critical role in the modern clinical management of HIV infection. This virus evolves rapidly within patients because of its error-prone reverse transcriptase and short generation time. Consequently, HIV variants with mutations that confer resistance to one or more antiretroviral drugs can emerge during sub-optimal treatment. There are now multiple HIV drug resistance interpretation algorithms that take the region of the HIV genome encoding the major drug targets as inputs; expert use of these algorithms can significantly improve to clinical outcomes in HIV treatment. Next-generation sequencing has the potential to revolutionize HIV resistance genotyping by lowering the threshold that rare but clinically significant HIV variants can be detected reproducibly, and by conferring improved cost-effectiveness in high-throughput scenarios. In this review, we discuss the relative merits and challenges of deploying the Illumina MiSeq instrument for clinical HIV genotyping.

An Efficient Microarray-Based Genotyping Platform for the Identification of Drug-Resistance Mutations in Majority and Minority Subpopulations of HIV-1 Quasispecies

The response of human immunodeficiency virus type 1 (HIV-1) quasispecies to antiretroviral therapy is influenced by the ensemble of mutants that composes the evolving population. Low-abundance subpopulations within HIV-1 quasispecies may determine the viral response to the administered drug combinations. However, routine sequencing assays available to clinical laboratories do not recognize HIV-1 minority variants representing less than 25% of the population. Although several alternative and more sensitive genotyping techniques have been developed, including next-generation sequencing (NGS) methods, they are usually very time consuming, expensive and require highly trained personnel, thus becoming unrealistic approaches in daily clinical practice. Here we describe the development and testing of a HIV-1 genotyping DNA microarray that detects and quantifies, in majority and minority viral subpopulations, relevant mutations and amino acid insertions in 42 codons of the pol gene associated with drug- and multidrug-resistance to protease (PR) and reverse transcriptase (RT) inhibitors. A customized bioinformatics protocol has been implemented to analyze the microarray hybridization data by including a new normalization procedure and a stepwise filtering algorithm, which resulted in the highly accurate (96.33%) detection of positive/negative signals. This microarray has been tested with 57 subtype B HIV-1 clinical samples extracted from multi-treated patients, showing an overall identification of 95.53% and 89.24% of the queried PR and RT codons, respectively, and enough sensitivity to detect minority subpopulations representing as low as 5–10% of the total quasispecies. The developed genotyping platform represents an efficient diagnostic and prognostic tool useful to personalize antiviral treatments in clinical practice.

MinVar: A rapid and versatile tool for HIV-1 drug resistance genotyping by deep sequencing

Genotypic monitoring of drug-resistance mutations (DRMs) in HIV-1 infected individuals is strongly recommended to guide selection of the initial antiretroviral therapy (ART) and changes of drug regimens. Traditionally, mutations conferring drug resistance are detected by population sequencing of the reverse transcribed viral RNA encoding the HIV-1 enzymes target by ART, followed by manual analysis and interpretation of Sanger sequencing traces. This process is labor intensive, relies on subjective interpretation from the operator, and offers limited sensitivity as only mutations above 20% frequency can be reliably detected. Here we present MinVar, a pipeline for the analysis of deep sequencing data, which allows reliable and automated detection of DRMs down to 5%. We evaluated MinVar with data from amplicon sequencing of defined mixtures of molecular virus clones with known DRM and plasma samples of viremic HIV-1 infected individuals and we compared it to VirVarSeq, another virus variant detection tool exclusively working on Illumina deep sequencing data. MinVar was designed to be compatible with a diverse range of sequencing platforms and allows the detection of DRMs and insertions/deletions from deep sequencing data without the need to perform additional bioinformatics analysis, a prerequisite to a widespread implementation of HIV-1 genotyping using deep sequencing in routine diagnostic settings.

Metabarcoding of Fecal Samples to Determine Herbivore Diets: A Case Study of the Endangered Pacific Pocket Mouse

Understanding the diet of an endangered species illuminates the animal’s ecology, habitat requirements, and conservation needs. However, direct observation of diet can be difficult, particularly for small, nocturnal animals such as the Pacific pocket mouse (Heteromyidae: Perognathus longimembris pacificus). Very little is known of the dietary habits of this federally endangered rodent, hindering management and restoration efforts. We used a metabarcoding approach to identify source plants in fecal samples (N = 52) from the three remaining populations known. The internal transcribed spacers (ITS) of the nuclear ribosomal loci were sequenced following the Illumina MiSeq amplicon strategy and processed reads were mapped to reference databases. We evaluated a range of threshold mapping criteria and found the best-performing setting generally recovered two distinct mock communities in proportions similar to expectation. We tested our method on captive animals fed a known diet and recovered almost all plant sources, but found substantial heterogeneity among fecal pellets collected from the same individual at the same time. Observed richness did not increase with pooling of pellets from the same individual. In field-collected samples, we identified 4–14 plant genera in individual samples and 74 genera overall, but over 50 percent of reads mapped to just six species in five genera. We simulated the effects of sequencing error, variable read length, and chimera formation to infer taxon-specific rates of misassignment for the local flora, which were generally low with some exceptions. Richness at the species and genus levels did not reach a clear asymptote, suggesting that diet breadth remained underestimated in the current pool of samples. Large numbers of scat samples are therefore needed to make inferences about diet and resource selection in future studies of the Pacific pocket mouse. We conclude that our minimally invasive method is promising for determining herbivore diets given a library of sequences from local plants.

Recent advances in inferring viral diversity from high-throughput sequencing data

Rapidly evolving RNA viruses prevail within a host as a collection of closely related variants, referred to as viral quasispecies. Advances in high-throughput sequencing (HTS) technologies have facilitated the assessment of the genetic diversity of such virus populations at an unprecedented level of detail. However, analysis of HTS data from virus populations is challenging due to short, error-prone reads. In order to account for uncertainties originating from these limitations, several computational and statistical methods have been developed for studying the genetic heterogeneity of virus population. Here, we review methods for the analysis of HTS reads, including approaches to local diversity estimation and global haplotype reconstruction. Challenges posed by aligning reads, as well as the impact of reference biases on diversity estimates are also discussed. In addition, we address some of the experimental approaches designed to improve the biological signal-to-noise ratio. In the future, computational methods for the analysis of heterogeneous virus populations are likely to continue being complemented by technological developments.

Contamination-controlled high-throughput whole genome sequencing for influenza A viruses using the MiSeq sequencer

Accurate full-length genomic sequences are important for viral phylogenetic studies. We developed a targeted high-throughput whole genome sequencing (HT-WGS) method for influenza A viruses, which utilized an enzymatic cleavage-based approach, the Nextera XT DNA library preparation kit, for library preparation. The entire library preparation workflow was adapted for the Sentosa SX101, a liquid handling platform, to automate this labor-intensive step. As the enzymatic cleavage-based approach generates low coverage reads at both ends of the cleaved products, we corrected this loss of sequencing coverage at the termini by introducing modified primers during the targeted amplification step to generate full-length influenza A sequences with even coverage across the whole genome. Another challenge of targeted HTS is the risk of specimen-to-specimen cross-contamination during the library preparation step that results in the calling of false-positive minority variants. We included an in-run, negative system control to capture contamination reads that may be generated during the liquid handling procedures. The upper limits of 99.99% prediction intervals of the contamination rate were adopted as cut-off values of contamination reads. Here, 148 influenza A/H3N2 samples were sequenced using the HTS protocol and were compared against a Sanger-based sequencing method. Our data showed that the rate of specimen-to-specimen cross-contamination was highly significant in HTS.

Impact of Pre-existing NS5A-L31 or -Y93H Minor Variants on Response Rates in Patients Infected with HCV Genotype-1b Treated with Daclatasvir/Asunaprevir

INTRODUCTION

The combination of daclatasvir (DCV, pan-genotypic NS5A inhibitor) plus asunaprevir (ASV; NS3 protease inhibitor) is approved in Japan, Korea and other countries for the treatment of chronic hepatitis C virus (HCV) genotype (GT)-1. A high (~90 to 100%) sustained virologic response (SVR) with DCV/ASV therapy has been achieved by excluding patients infected with HCV GT-1b with baseline NS5A resistance-associated variants (RAVs) at L31 or Y93H detected by direct sequencing (DS). We set out to determine whether patients with minor variants at NS5A-L31 or -Y93H, detected by next-generation sequencing (NGS), impacted SVR rates with DCV/ASV therapy.

METHODS

Baseline samples from 222 interferon (IFN)-ineligible/intolerant (N = 135) and prior non-responder (N = 87) patients infected with GT-1b who were treated with DCV/ASV for 24 weeks in the Phase 3 clinical study AI447026 were prepared for NGS (Ion-Torrent platform). The prevalence of baseline NS5A RAVs and their impact on SVR when observed at ≥1% by NGS in a patient's virus population were examined. NGS and DS (sensitivity ≥20%) data were compared.

RESULTS

The prevalence of baseline NS5A RAVs at L31 or Y93H was 29% (63/219) and 18% (39/214) by NGS and DS, respectively. SVR24 rates were comparable in patients without observed baseline L31 or Y93H polymorphisms whether assessed by NGS (96%; 148/154) or by the less sensitive DS platform (95%; 164/173).

CONCLUSION

Optimal SVR rates (≥95%) to DCV/ASV treatment were achieved using DS to exclude patients infected with GT-1b with NS5A RAVs at L31 or Y93H representing ≥20% of their virus population. Exclusion by NGS of patients with minor variants in NS5A (<20%) did not enhance SVR rates. These results suggest that the presence of minor variants in NS5A does not appear to impact the overall SVR rate in patients with GT-1b treated with DCV/ASV.

FUNDING

This study was sponsored by Bristol-Myers Squibb.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01497834.

Effects of long-term tenofovir-based combination antiretroviral therapy in HIV-hepatitis B virus coinfection on persistent hepatitis B virus viremia and the role of hepatitis B virus quasispecies diversity

OBJECTIVE

Hepatitis B virus (HBV) can persist in some HIV-HBV coinfected individuals on tenofovir disoproxil fumarate (TDF)-containing combination antiretroviral therapy (cART) but HBV resistance to TDF has not been reported and the source of persistent HBV DNA on TDF is poorly understood. The aims of this study were to assess long-term HBV suppression in HIV-HBV coinfected individuals receiving TDF and investigate quasispecies variation using ultradeep pyrosequencing (UDPS).

METHODS

Ninety-two HIV-HBV coinfected participants on, or about to commence, TDF-containing cART were enrolled [Australia (n = 40), Thailand (n = 52)] and followed for 2 years with study visits every 6 months. HBV reverse transcriptase sequencing was performed on samples with HBV DNA more than 400 IU/ml by population-based methods and UDPS. Quasispecies diversity was assessed using Shannon entropy.

RESULTS

Over 24 months, viremia was detected at least once in 17% (n = 16) of the cohort. Novel mutations were not identified in on TDF samples tested by population-based sequencing (n = 19). Using UDPS, the median Shannon entropy value in samples prior to TDF in patients aviremic on TDF was not statistically different from those who were viremic on TDF (n = 50; 8.4 and 9.1, respectively, P = 0.9). Longitudinal Shannon entropy analysis of on TDF samples from five participants showed three individuals with significant changes in viral diversity over time.

CONCLUSION

Persistent viremia on TDF-containing cART is common but TDF-resistance was not detected. In some individuals, changes in viral diversity over time were observed on TDF which could potentially be active viral replication. Further follow-up will be needed to determine the clinical significance of detectable HBV DNA on TDF-containing cART.

High-specificity detection of rare alleles with Paired-End Low Error Sequencing (PELE-Seq)

BACKGROUND

Polymorphic loci exist throughout the genomes of a population and provide the raw genetic material needed for a species to adapt to changes in the environment. The minor allele frequencies of rare Single Nucleotide Polymorphisms (SNPs) within a population have been difficult to track with Next-Generation Sequencing (NGS), due to the high error rate of standard methods such as Illumina sequencing.

RESULTS

We have developed a wet-lab protocol and variant-calling method that identifies both sequencing and PCR errors, called Paired-End Low Error Sequencing (PELE-Seq). To test the specificity and sensitivity of the PELE-Seq method, we sequenced control E. coli DNA libraries containing known rare alleles present at frequencies ranging from 0.2-0.4 % of the total reads. PELE-Seq had higher specificity and sensitivity than standard libraries. We then used PELE-Seq to characterize rare alleles in a Caenorhabditis remanei nematode worm population before and after laboratory adaptation, and found that minor and rare alleles can undergo large changes in frequency during lab-adaptation.

CONCLUSION

We have developed a method of rare allele detection that mitigates both sequencing and PCR errors, called PELE-Seq. PELE-Seq was evaluated using control E. coli populations and was then used to compare a wild C. remanei population to a lab-adapted population. The PELE-Seq method is ideal for investigating the dynamics of rare alleles in a broad range of reduced-representation sequencing methods, including targeted amplicon sequencing, RAD-Seq, ddRAD, and GBS. PELE-Seq is also well-suited for whole genome sequencing of mitochondria and viruses, and for high-throughput rare mutation screens.

Differences in the Selection Bottleneck between Modes of Sexual Transmission Influence the Genetic Composition of the HIV-1 Founder Virus

Due to the stringent population bottleneck that occurs during sexual HIV-1 transmission, systemic infection is typically established by a limited number of founder viruses. Elucidation of the precise forces influencing the selection of founder viruses may reveal key vulnerabilities that could aid in the development of a vaccine or other clinical interventions. Here, we utilize deep sequencing data and apply a genetic distance-based method to investigate whether the mode of sexual transmission shapes the nascent founder viral genome. Analysis of 74 acute and early HIV-1 infected subjects revealed that 83% of men who have sex with men (MSM) exhibit a single founder virus, levels similar to those previously observed in heterosexual (HSX) transmission. In a metadata analysis of a total of 354 subjects, including HSX, MSM and injecting drug users (IDU), we also observed no significant differences in the frequency of single founder virus infections between HSX and MSM transmissions. However, comparison of HIV-1 envelope sequences revealed that HSX founder viruses exhibited a greater number of codon sites under positive selection, as well as stronger transmission indices possibly reflective of higher fitness variants. Moreover, specific genetic “signatures” within MSM and HSX founder viruses were identified, with single polymorphisms within gp41 enriched among HSX viruses while more complex patterns, including clustered polymorphisms surrounding the CD4 binding site, were enriched in MSM viruses. While our findings do not support an influence of the mode of sexual transmission on the number of founder viruses, they do demonstrate that there are marked differences in the selection bottleneck that can significantly shape their genetic composition. This study illustrates the complex dynamics of the transmission bottleneck and reveals that distinct genetic bottleneck processes exist dependent upon the mode of HIV-1 transmission.

While the global spread of HIV-1 has been fueled by sexual transmission the genetic determinants underlying the transmission bottleneck remains poorly understood. Here we characterized founder virus population diversity from next generation sequencing data in a cohort of 74 acute and early HIV-1 infected individuals. We observe that the risk of multi-variant infection in men-who-have-sex-with-men (MSM) is not greater than that observed for heterosexuals (HSX), contrary to reports of higher rates of multiple founder virus infections in higher-risk MSM transmissions. These findings were further supported through a metadata analysis of 354 acute and early HIV-1 subjects. We did, however, observe differences between HSM and MSM founder viruses, including a higher selection barrier in HSX transmission with founder viruses being more cohort consensus-like that may be reflective of increased replicative fitness. We also identified a number of residues within Envelope that behave in a risk-dependent manner and could be key for HIV-1 transmission. These novel insights improve our understanding of the HIV-1 transmission bottleneck and underscore the differential selective pressures that founder viruses within the two major transmission risk groups are subjected to.

Reproducibility of Illumina platform deep sequencing errors allows accurate determination of DNA barcodes in cells

Background

Next generation sequencing (NGS) of amplified DNA is a powerful tool to describe genetic heterogeneity within cell populations that can both be used to investigate the clonal structure of cell populations and to perform genetic lineage tracing. For applications in which both abundant and rare sequences are biologically relevant, the relatively high error rate of NGS techniques complicates data analysis, as it is difficult to distinguish rare true sequences from spurious sequences that are generated by PCR or sequencing errors. This issue, for instance, applies to cellular barcoding strategies that aim to follow the amount and type of offspring of single cells, by supplying these with unique heritable DNA tags.

Results

Here, we use genetic barcoding data from the Illumina HiSeq platform to show that straightforward read threshold-based filtering of data is typically insufficient to filter out spurious barcodes. Importantly, we demonstrate that specific sequencing errors occur at an approximately constant rate across different samples that are sequenced in parallel. We exploit this observation by developing a novel approach to filter out spurious sequences.

Conclusions

Application of our new method demonstrates its value in the identification of true sequences amongst spurious sequences in biological data sets.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0999-4) contains supplementary material, which is available to authorized users.

Benefits and Challenges with Applying Unique Molecular Identifiers in Next Generation Sequencing to Detect Low Frequency Mutations

Indexing individual template molecules with a unique identifier (UID) before PCR and deep sequencing is promising for detecting low frequency mutations, as true mutations could be distinguished from PCR errors or sequencing errors based on consensus among reads sharing same index. In an effort to develop a robust assay to detect from urine low-abundant bladder cancer cells carrying well-documented mutations, we have tested the idea first on a set of mock templates, with wild type and known mutants mixed at defined ratios. We have measured the combined error rate for PCR and Illumina sequencing at each nucleotide position of three exons, and demonstrated the power of a UID in distinguishing and correcting errors. In addition, we have demonstrated that PCR sampling bias, rather than PCR errors, challenges the UID-deep sequencing method in faithfully detecting low frequency mutation.

Ultra-deep sequencing of VHSV isolates contributes to understanding the role of viral quasispecies

The high mutation rate of RNA viruses enables the generation of a genetically diverse viral population, termed a quasispecies, within a single infected host. This high in-host genetic diversity enables an RNA virus to adapt to a diverse array of selective pressures such as host immune response and switching between host species. The negative-sense, single-stranded RNA virus, viral haemorrhagic septicaemia virus (VHSV), was originally considered an epidemic virus of cultured rainbow trout in Europe, but was later proved to be endemic among a range of marine fish species in the Northern hemisphere. To better understand the nature of a virus quasispecies related to the evolutionary potential of VHSV, a deep-sequencing protocol specific to VHSV was established and applied to 4 VHSV isolates, 2 originating from rainbow trout and 2 from Atlantic herring. Each isolate was subjected to Illumina paired end shotgun sequencing after PCR amplification and the 11.1 kb genome was successfully sequenced with an average coverage of 0.5-1.9 × 10(6) sequenced copies. Differences in single nucleotide polymorphism (SNP) frequency were detected both within and between isolates, possibly related to their stage of adaptation to host species and host immune reactions. The N, M, P and Nv genes appeared nearly fixed, while genetic variation in the G and L genes demonstrated presence of diverse genetic populations particularly in two isolates. The results demonstrate that deep sequencing and analysis methodologies can be useful for future in vivo host adaption studies of VHSV.

Denoising DNA deep sequencing data-high-throughput sequencing errors and their correction

Characterizing the errors generated by common high-throughput sequencing platforms and telling true genetic variation from technical artefacts are two interdependent steps, essential to many analyses such as single nucleotide variant calling, haplotype inference, sequence assembly and evolutionary studies. Both random and systematic errors can show a specific occurrence profile for each of the six prominent sequencing platforms surveyed here: 454 pyrosequencing, Complete Genomics DNA nanoball sequencing, Illumina sequencing by synthesis, Ion Torrent semiconductor sequencing, Pacific Biosciences single-molecule real-time sequencing and Oxford Nanopore sequencing. There is a large variety of programs available for error removal in sequencing read data, which differ in the error models and statistical techniques they use, the features of the data they analyse, the parameters they determine from them and the data structures and algorithms they use. We highlight the assumptions they make and for which data types these hold, providing guidance which tools to consider for benchmarking with regard to the data properties. While no benchmarking results are included here, such specific benchmarks would greatly inform tool choices and future software development. The development of stand-alone error correctors, as well as single nucleotide variant and haplotype callers, could also benefit from using more of the knowledge about error profiles and from (re)combining ideas from the existing approaches presented here.

Short Communication: Investigating a Chain of HIV Transmission Events Due to Homosexual Exposure and Blood Transfusion Based on a Next Generation Sequencing Method

This study investigates a chain of HIV transmission events due to homosexual exposure and blood transfusion in China. The MiSeq platform, a next generation sequencing (NGS) system, was used to obtain genetic details of the HIV-1 env region (336 base pairs). Evolutionary analysis combined with epidemiologic evidence suggests a transmission chain from patient T3 to T2 through homosexual exposure and subsequently to T1 through blood transfusion. More importantly, a phylogenetic study suggested a likely genetic bottleneck for HIV in homosexual transmission from T3 to T2, while T1 inherited the majority of variants from T2. The result from the MiSeq platform is consistent with findings from the epidemiologic survey. The MiSeq platform is a powerful tool for tracing HIV transmissions and intrapersonal evolution.

Nature and Extent of Genetic Diversity of Dengue Viruses Determined by 454 Pyrosequencing

Dengue virus (DENV) populations are characteristically highly diverse. Regular lineage extinction and replacement is an important dynamic DENV feature, and most DENV lineage turnover events are associated with increased incidence of disease. The role of genetic diversity in DENV lineage extinctions is not understood. We investigated the nature and extent of genetic diversity in the envelope (E) gene of DENV serotype 1 representing different lineages histories. A region of the DENV genome spanning the E gene was amplified and sequenced by Roche/454 pyrosequencing. The pyrosequencing results identified distinct sub-populations (haplotypes) for each DENV-1 E gene. A phylogenetic tree was constructed with the consensus DENV-1 E gene nucleotide sequences, and the sequences of each constructed haplotype showed that the haplotypes segregated with the Sanger consensus sequence of the population from which they were drawn. Haplotypes determined through pyrosequencing identified a recombinant DENV genome that could not be identified through Sanger sequencing. Nucleotide level sequence diversities of DENV-1 populations determined from SNP analysis were very low, estimated from 0.009–0.01. There were also no stop codon, frameshift or non-frameshift mutations observed in the E genes of any lineage. No significant correlations between the accumulation of deleterious mutations or increasing genetic diversity and lineage extinction were observed (p>0.5). Although our hypothesis that accumulation of deleterious mutations over time led to the extinction and replacement of DENV lineages was ultimately not supported by the data, our data does highlight the significant technical issues that must be resolved in the way in which population diversity is measured for DENV and other viruses. The results provide an insight into the within-population genetic structure and diversity of DENV-1 populations.